{
\def\sym#1{\ifmmode^{#1}\else\(^{#1}\)\fi}
\begin{tabular}{l*{3}{c}}
\hline\hline
            &\multicolumn{1}{c}{(1)}&\multicolumn{1}{c}{(2)}&\multicolumn{1}{c}{(3)}\\
            &\multicolumn{1}{c}{2014-2019}&\multicolumn{1}{c}{2009-2019}&\multicolumn{1}{c}{2009-2019}\\
\hline
2019 election&       3.974\sym{***}&      -5.130\sym{***}&      -14.82\sym{***}\\
            &     (0.270)         &     (0.288)         &     (0.373)         \\
[1em]
EP election in 2019&       3.229\sym{***}&       4.368\sym{***}&       4.443\sym{***}\\
            &     (0.338)         &     (0.344)         &     (0.337)         \\
[1em]
Ciutadella in 2019&      -10.11\sym{***}&      -9.277\sym{***}&      -8.798\sym{***}\\
            &     (0.477)         &     (0.461)         &     (0.462)         \\
[1em]
EP 2019 x Ciutadella&      -5.150\sym{***}&      -5.958\sym{***}&      -6.032\sym{***}\\
            &     (1.023)         &     (0.958)         &     (0.955)         \\
[1em]
2014-2015 election&                     &                     &      -18.43\sym{***}\\
            &                     &                     &     (0.286)         \\
\hline
\(N\)       &        4098         &        6053         &        6053         \\
\hline\hline
\multicolumn{4}{l}{\footnotesize Standard errors in parentheses}\\
\multicolumn{4}{l}{\footnotesize All models include voting station * election type fixed effects}\\
\multicolumn{4}{l}{\footnotesize Standard errors are clustered by voting station * election type}\\
\multicolumn{4}{l}{\footnotesize \sym{*} \(p<0.10\), \sym{**} \(p<0.05\), \sym{***} \(p<0.01\)}\\
\end{tabular}
}
